Amostras instrumentais

import warnings
warnings.simplefilter('ignore')
import IPython.display as ipd
import librosa
%matplotlib inline
import matplotlib.pyplot as plt
import librosa.display
import numpy as np
print('ContraBaixo')
ipd.Audio('../_static/audio/cb.wav')
ContraBaixo
x, sr = librosa.load('../_static/audio/cb.wav', duration=0.02)
plt.figure(figsize=(14, 10))
librosa.display.waveplot(x, sr=sr, alpha=0.8)
<matplotlib.collections.PolyCollection at 0x7f01ffe18940>
../_images/instrumental_samples_3_1.png
S = librosa.feature.melspectrogram(y=x, sr=sr, n_mels=128,
                                    fmax=8000)
plt.figure(figsize=(14, 5))
S_dB = librosa.power_to_db(S, ref=np.max)
librosa.display.specshow(S_dB, sr=sr, x_axis='time', y_axis='hz')
plt.colorbar(format='%+2.0f dB')
plt.title('Mel-frequency spectrogram')
plt.tight_layout()
plt.show()
../_images/instrumental_samples_4_0.png
print('ContraBaixo e Flauta')
ipd.Audio('../_static/audio/cbfl.wav')
ContraBaixo e Flauta
x, sr = librosa.load('../_static/audio/cbfl.wav', duration=0.02)
plt.figure(figsize=(14, 10))
librosa.display.waveplot(x, sr=sr, alpha=0.8)
<matplotlib.collections.PolyCollection at 0x7f01ff967b20>
../_images/instrumental_samples_6_1.png
S = librosa.feature.melspectrogram(y=x, sr=sr, n_mels=128,
                                    fmax=8000)
plt.figure(figsize=(14, 5))
S_dB = librosa.power_to_db(S, ref=np.max)
librosa.display.specshow(S_dB, sr=sr, x_axis='time', y_axis='hz')
plt.colorbar(format='%+2.0f dB')
plt.title('Mel-frequency spectrogram')
plt.tight_layout()
plt.show()
../_images/instrumental_samples_7_0.png
print('Trompa')
ipd.Audio('../_static/audio/fh.wav')
Trompa
x, sr = librosa.load('../_static/audio/fh.wav', duration=0.02)
plt.figure(figsize=(14, 10))
librosa.display.waveplot(x, sr=sr, alpha=0.8)
<matplotlib.collections.PolyCollection at 0x7f01ff86ff40>
../_images/instrumental_samples_9_1.png
S = librosa.feature.melspectrogram(y=x, sr=sr, n_mels=128,
                                    fmax=8000)
plt.figure(figsize=(14, 5))
S_dB = librosa.power_to_db(S, ref=np.max)
librosa.display.specshow(S_dB, sr=sr, x_axis='time', y_axis='hz')
plt.colorbar(format='%+2.0f dB')
plt.title('Mel-frequency spectrogram')
plt.tight_layout()
plt.show()
../_images/instrumental_samples_10_0.png
print('Flauta')
ipd.Audio('../_static/audio/fl.wav')
Flauta
x, sr = librosa.load('../_static/audio/fl.wav', duration=0.02)
plt.figure(figsize=(14, 10))
librosa.display.waveplot(x, sr=sr, alpha=0.8)
<matplotlib.collections.PolyCollection at 0x7f01ffac47f0>
../_images/instrumental_samples_12_1.png
S = librosa.feature.melspectrogram(y=x, sr=sr, n_mels=128,
                                    fmax=8000)
plt.figure(figsize=(14, 5))
S_dB = librosa.power_to_db(S, ref=np.max)
librosa.display.specshow(S_dB, sr=sr, x_axis='time', y_axis='hz')
plt.colorbar(format='%+2.0f dB')
plt.title('Mel-frequency spectrogram')
plt.tight_layout()
plt.show()
../_images/instrumental_samples_13_0.png
print('Harpa')
ipd.Audio('../_static/audio/hp.wav')
Harpa
x, sr = librosa.load('../_static/audio/hp.wav', duration=0.02)
plt.figure(figsize=(14, 10))
librosa.display.waveplot(x, sr=sr, alpha=0.8)
<matplotlib.collections.PolyCollection at 0x7f01ffbc5ee0>
../_images/instrumental_samples_15_1.png
S = librosa.feature.melspectrogram(y=x, sr=sr, n_mels=128,
                                    fmax=8000)
plt.figure(figsize=(14, 5))
S_dB = librosa.power_to_db(S, ref=np.max)
librosa.display.specshow(S_dB, sr=sr, x_axis='time', y_axis='hz')
plt.colorbar(format='%+2.0f dB')
plt.title('Mel-frequency spectrogram')
plt.tight_layout()
plt.show()
../_images/instrumental_samples_16_0.png
print('Harpa e Trompa')
ipd.Audio('../_static/audio/hpfh.wav')
Harpa e Trompa
x, sr = librosa.load('../_static/audio/hpfh.wav', duration=0.02)
plt.figure(figsize=(14, 10))
librosa.display.waveplot(x, sr=sr, alpha=0.8)
<matplotlib.collections.PolyCollection at 0x7f01ffb51ee0>
../_images/instrumental_samples_18_1.png
S = librosa.feature.melspectrogram(y=x, sr=sr, n_mels=128,
                                    fmax=8000)
plt.figure(figsize=(14, 5))
S_dB = librosa.power_to_db(S, ref=np.max)
librosa.display.specshow(S_dB, sr=sr, x_axis='time', y_axis='hz')
plt.colorbar(format='%+2.0f dB')
plt.title('Mel-frequency spectrogram')
plt.tight_layout()
plt.show()
../_images/instrumental_samples_19_0.png
print('Mistura')
ipd.Audio('../_static/audio/mistura.wav')
Mistura
x, sr = librosa.load('../_static/audio/mistura.wav', duration=0.02)
plt.figure(figsize=(14, 10))
librosa.display.waveplot(x, sr=sr, alpha=0.8)
<matplotlib.collections.PolyCollection at 0x7f01ff7d94c0>
../_images/instrumental_samples_21_1.png
S = librosa.feature.melspectrogram(y=x, sr=sr, n_mels=128,
                                    fmax=8000)
plt.figure(figsize=(14, 5))
S_dB = librosa.power_to_db(S, ref=np.max)
librosa.display.specshow(S_dB, sr=sr, x_axis='time', y_axis='hz')
plt.colorbar(format='%+2.0f dB')
plt.title('Mel-frequency spectrogram')
plt.tight_layout()
plt.show()
../_images/instrumental_samples_22_0.png